Applied Maths of Neural Networks -- books and papers?

[s00mb]

Does anyone know any good up to date books on the mathematics of neural networks? If you know any good research papers that would be cool too. I've read through "Intro to the theory of neural computation" by John Hertz but it's a 1991 book. I'm looking for generalized theorems on optimizing/minimizing the placement and number of neurons in the network assuming some given way of calculating the weights. Also, if you know any cool research papers I'd like to know them. I've already seen the one on changing one pixel input to confuse a NN though. Geometry and Differential Equations (especially fractional applications) a plus. I've been browsing the internet for it and figured I'd try to pick your brains for it while I am at it. Thanks in advance.

 

[jedishrfu]

There's a lot of books out there. The one I like is:

Hands-on Machine Learning with Scikit-Learn, Keras and Tensorflow

It likely has some interesting math in it although most books skip past the details and go for the practice more. People want to use the algorithms to do cool stuff and leave the math to the developers of these packages.

Another book of interest would be:

Algorithms for Optimization

which covers many of the algorithms used in machine learning. All the code is written in Julia.

 

[s00mb]

Yeah, I've read through most of the "practical" books, I was looking for rigorous books with proofs. Ohhh bonus points for using Julia I like that I'll have to check it out just for that :)